Abstract
The mineralogical complexity of mine dust complicates exposure monitoring methods for occupational, respirable hazards. Improved understanding of the variability in respirable dust characteristics, e.g., mineral phase occurrence and composition, is required to advance on-site monitoring techniques that can be applied across diverse mining sectors. Principal components analysis (PCA) models were applied separately to XRD and FTIR datasets collected on 130 respirable dust samples from seven mining commodities to explore similarities and differences among the samples. Findings from both PCA models classified limestone, iron, and granite mine samples via their analytical responses. However, the results also cautioned that respirable samples from these commodities may not always fit patterns observed within the model. For example, one unique sample collected in a limestone mine contained no carbonate minerals. Future predictive quantification models should account for unique samples. Differences between gold and copper mine dust samples were difficult to observe. Further investigation suggested that the key to their differentiation by FTIR may lie in the characterization of clays. The results presented in this study provide foundational information for guiding the development of quantification models for respirable mineral hazards in the mining industry.
Subject
Geology,Geotechnical Engineering and Engineering Geology
Cited by
7 articles.
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